A Bayesian Approach to Deriving Ceres Surface Composition from Dawn VIR Data: Initial Quantification of Bright Spot and Typical Dark Material Phases with this Method-猫眼课题宝

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2018-03

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H. Kurokawa;B. Ehlmann;E. Ammannito;M. C. Sanctis;M. Lapôtre;T. Usui;N. Stein;T. Prettyman;A. Raponi;M. Ciarniello

与 Dawn VIR 数据（红色）相比，模型反射率（黑色）的终端成员。丰度 PDF（蓝色）与 [7]（绿色）中的值相比表明，我们的方法可以表征适合数据的成分范围。非对角丰度图显示可接受解决方案中端元之间的相关性（或缺乏相关性）。从 DAWN VIR 数据推导谷神星表面成分的贝叶斯方法：用该方法对亮点和典型暗物质相进行初始量化。 H.黑川，B.L.埃尔曼，E.阿曼尼托，M.C. De Sanctis, M. Lapotre, T. Usui, N.T. Stein、T. Prettyman、A. Raponi、M. Ciarniello、ELSI、东京理工大学；加州理工学院-GPS；喷气推进实验室/加州理工学院； ASI，罗马 IAPS-INAF，罗马；哈佛大学； PSI

end members with model reflectance (black) compared to Dawn VIR data (red). PDFs of the abundances (blue) compared to the values from [7] (green) show that our approach allows characterization of the range of compositions that can fit the data. Non-diagonal abundance plots show the correlations (or lack thereof) between endmembers in the acceptable solutions. A BAYESIAN APPROACH TO DERIVING CERES SURFACE COMPOSITION FROM DAWN VIR DATA: INITIAL QUANTIFICATION OF BRIGHT SPOT AND TYPICAL DARK MATERIAL PHASES WITH THIS METHOD. H. Kurokawa, B.L. Ehlmann, E. Ammannito, M.C. De Sanctis, M. Lapotre, T. Usui, N.T. Stein, T. Prettyman, A. Raponi, M. Ciarniello, ELSI, Tokyo Tech; Caltech-GPS; JPL/Caltech; ASI, Rome IAPS-INAF, Rome; Harvard University; PSI

A Bayesian Approach to Deriving Ceres Surface Composition from Dawn VIR Data: Initial Quantification of Bright Spot and Typical Dark Material Phases with this Method

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